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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">ppharm</journal-id><journal-title-group><journal-title xml:lang="ru">Педиатрическая фармакология</journal-title><trans-title-group xml:lang="en"><trans-title>Pediatric pharmacology</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1727-5776</issn><issn pub-type="epub">2500-3089</issn><publisher><publisher-name>Издательство «ПедиатрЪ»</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.15690/pf.v16i6.2073</article-id><article-id custom-type="elpub" pub-id-type="custom">ppharm-1790</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОРИГИНАЛЬНЫЕ СТАТЬИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ORIGINAL ARTICLES</subject></subj-group></article-categories><title-group><article-title>Связь когнитивного и социального функционирования школьников: изучение популяционных данных с помощью методов интеллектуального анализа разнородных данных</article-title><trans-title-group xml:lang="en"><trans-title>Correlations Between Cognitive and Social Functioning of Schoolchildren: Study of Population Data Using methods of intellectual Analysis of heterogeneous Data</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2209-7531</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Намазова-Баранова</surname><given-names>Л. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Namazova-Baranova</surname><given-names>Leyla S.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8540-3858</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Каркашадзе</surname><given-names>Г. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Karkashadze</surname><given-names>Georgiy A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Контактная информация: Каркашадзе Георгий Арчилович, кандидат медицинских наук, руководитель отделом развития мозга в онтогенезе, формирования когнитивных функций и нейробиологии НИИ педиатрии и охраны здоровья детей ЦКБ РАН</p></bio><bio xml:lang="en"/><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-7398-0562</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Вишнёва</surname><given-names>Е. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Vishnyova</surname><given-names>Elena A.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0039-943X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Молодченко</surname><given-names>А. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Molodchenko</surname><given-names>A. I.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Научно-исследовательский институт педиатрии и охраны здоровья детей ЦКБ Российской академии наук</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Central Clinical Hospital of the Russian Academy of Sciences</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Федеральный исследовательский центр «Информатика и управление» Российской академии наук</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Federal Research Center «Computer Science and Control» of the Russian Academy of Sciences</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2019</year></pub-date><pub-date pub-type="epub"><day>21</day><month>02</month><year>2020</year></pub-date><volume>16</volume><issue>6</issue><fpage>353</fpage><lpage>365</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Намазова-Баранова Л.С., Каркашадзе Г.А., Вишнёва Е.А., Молодченко А.И., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Намазова-Баранова Л.С., Каркашадзе Г.А., Вишнёва Е.А., Молодченко А.И.</copyright-holder><copyright-holder xml:lang="en">Namazova-Baranova L.S., Karkashadze G.A., Vishnyova E.A., Molodchenko A.I.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.pedpharma.ru/jour/article/view/1790">https://www.pedpharma.ru/jour/article/view/1790</self-uri><abstract><sec><title>Обоснование</title><p>Обоснование. Комплексная оценка состояния психики детского населения в популяционном масштабе необходима для разработки мероприятий в целях оптимального формирования будущего потенциала страны. Однако изучение имеющейся связи когнитивных и социально-характерологических параметров формирующейся личности в популяционном масштабе обусловлено трудностями сбора информации и низкой эффективностью традиционных методов анализа.</p><p> Цель исследования — изучить взаимосвязь уровня когнитивной деятельности и социального функционирования школьников с помощью кластерного анализа и алгоритмов машинного обучения. </p></sec><sec><title>Методы</title><p>Методы. В исследование включали школьников 5-х и 9-х классов, обучавшихся в среднеобразовательных школах 8 крупных городов России. Для обследования использовали батарею тестов по оценке когнитивной деятельности и вопросник внешкольной жизнедеятельности, который заполняли родители. Анализ проводили с помощью кластеризации и методов машинного обучения.</p></sec><sec><title>Результаты исследования</title><p>Результаты исследования. С помощью батареи когнитивных тестов было обследовано 1983 школьника 5-х и 9-х классов, при этом из числа их родителей 1171 заполнили вопросник внешкольной жизнедеятельности. Были выделены два кластера разного уровня когнитивной успешности детей и подростков в обеих возрастных группах. Установлено, что высокий уровень когнитивной деятельности связан с посещением музыкальной школы, неспортивными увлечениями в целом у школьников обеих возрастных групп; дополнительно к этому — с увлечением баскетболом, футболом, танцами, летним отдыхом в классических лагерях у школьников 5-х классов; увлечением плаванием, горными лыжами, спортом на уровне дворовых состязаний, сочетанием занятий с репетиторами и компьютерным программированием — у школьников 9-х классов. </p></sec><sec><title>Заключение</title><p>Заключение. Установлены связи уровня когнитивной деятельности с индивидуальной типологией внеучебной жизнедеятельности, в основе которой лежат особенности формирования личности и социальное влияние семьи.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Background</title><p>Background. The comprehensive assessment of mentality in children on the population scale is necessary to develop measures for optimal shaping of the country’s future potential. However, the correlations between cognitive and socio-characterological parameters of the emerging personality makes it difficult to collect information and decreases the efficiency of traditional analysis methods on the population scale. </p><p>The aim of the study is to estimate the correlations between cognitive activity social functioning of schoolchildren using artificial intelligence methods. </p></sec><sec><title>Methods</title><p>Methods. The study included schoolchildren from 5th and 9th grades who studied in secondary schools in 8 major Russian cities. The survey used a battery of tests to assess cognitive performance and a questionnaire of extracurricular activities which was completed by parents. The analysis was performed using clustering and machine learning methods. </p></sec><sec><title>Results</title><p>Results. The battery of cognitive tests was used to examine 1983 children from 5th and 9th grades. Parents of 1,171 of them completed the extracurricular activity questionnaire. Two clusters of different levels of cognitive success of children and adolescents in both age groups were identified. The high level of cognitive activity was determined in cases associated with attending music school, non-sports hobbies in schoolchildren of both age groups in general; basketball, football, dancing, summer holidays in camps in 5th grade schoolchildren; and swimming, skiing, competitive sports (non-professional), tutoring sections, computer programming in 9th grade schoolchildren.</p></sec><sec><title> Conclusion</title><p> Conclusion. The correlations between the level of cognitive activity and the individual typology of extracurricular activities (based on features of personality formation and social influence of the family) has been determined.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>машинное обучение</kwd><kwd>дети</kwd><kwd>подростки</kwd><kwd>когнитивная деятельность</kwd><kwd>социальное функционирование</kwd><kwd>популяция</kwd></kwd-group><kwd-group xml:lang="en"><kwd>machine learning</kwd><kwd>children</kwd><kwd>adolescents</kwd><kwd>cognitive activity</kwd><kwd>social functioning</kwd><kwd>population</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Работа выполнена при частичной поддержке гранта РФФИ (17-29-02501 офи_м).</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Баранов А.А., Намазова-Баранова Л.С., Ильин А.Г. 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